Retrieve either a single or many Gains/Lift tables from H2O objects.
Usage
h2o.gainsLift(object, ...)
h2o.gains_lift(object, ...)
# S4 method for class 'H2OModel'
h2o.gainsLift(object, newdata, valid = FALSE, xval = FALSE, ...)
# S4 method for class 'H2OModelMetrics'
h2o.gainsLift(object)Arguments
- object
Either an H2OModel object or an H2OModelMetrics object.
- ...
further arguments to be passed to/from this method.
- newdata
An H2OFrame object that can be scored on. Requires a valid response column.
- valid
Retrieve the validation metric.
- xval
Retrieve the cross-validation metric.
Value
Calling this function on H2OModel objects returns a
Gains/Lift table corresponding to the predict function.
Details
The H2OModelMetrics version of this function will only take H2OBinomialMetrics objects.
See also
predict for generating prediction frames,
h2o.performance for creating
H2OModelMetrics.
Examples
if (FALSE) { # \dontrun{
library(h2o)
h2o.init()
prostate_path <- system.file("extdata", "prostate.csv", package = "h2o")
prostate <- h2o.uploadFile(prostate_path)
prostate[, 2] <- as.factor(prostate[, 2])
model <- h2o.gbm(x = 3:9, y = 2, distribution = "bernoulli",
training_frame = prostate, validation_frame = prostate, nfolds = 3)
h2o.gainsLift(model) ## extract training metrics
h2o.gainsLift(model, valid = TRUE) ## extract validation metrics (here: the same)
h2o.gainsLift(model, xval = TRUE) ## extract cross-validation metrics
h2o.gainsLift(model, newdata = prostate) ## score on new data (here: the same)
# Generating a ModelMetrics object
perf <- h2o.performance(model, prostate)
h2o.gainsLift(perf) ## extract from existing metrics object
} # }